naukri
Product Engineering Head
Intelmatix
Riyadh, KSA
Parttime
Senior
4 months ago
Product Engineering Head
Free
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Product Engineering Head
About the Role
Key Responsibilities: Product-Engineering Partnership & Strategy Partner closely with the Product Management team as the senior engineering leader to translate product vision, s.
Key Skills for This Role
Product Engineering Head
Full Job Posting
Product-Engineering Partnership & Strategy
- Partner closely with the Product Management team as the senior engineering leader to translate product vision, strategy, and roadmap into executable engineering plans and deliverables.
- Participate in product strategy discussions, roadmap planning sessions, and product prioritization decisions providing technical perspective on feasibility, effort, trade-offs, and innovation opportunities.
- Collaborate with Product Management to define product requirements, acceptance criteria, and success metrics ensuring shared understanding between product vision and engineering execution.
- Provide technical input and engineering perspective during product discovery, user research synthesis, and feature conceptualization helping shape product decisions with engineering insights on what's possible, scalable, and innovative.
- Balance product ambition with engineering pragmatism identifying opportunities to deliver breakthrough user value while managing technical complexity, debt, and platform stability.
- Champion engineering excellence and platform thinking in product discussions ensuring product decisions consider long-term architectural health, technical debt management, scalability requirements, and engineering sustainability.
Platform Architecture & Technical Leadership
- Own the technical architecture and platform strategy for all products and AI agents ensuring scalable, secure, maintainable, and performant multi-tenant systems.
- Define and drive the evolution of core platform capabilities, shared services, component libraries, design systems, and engineering infrastructure that accelerate product development velocity.
- Make critical architectural decisions on technology choices, system design patterns, data architecture, API contracts, integration strategies, and infrastructure approaches balancing innovation, proven technologies, and team capabilities.
- Establish and maintain engineering standards, architectural principles, design patterns, security guidelines, and quality benchmarks that ensure consistency and excellence across the product engineering organization.
- Drive technical innovation in AI/ML model deployment, real-time data processing, intelligent automation, and Decision Intelligence capabilities that differentiate our products in the market.
- Lead architectural reviews, technology evaluations, and technical risk assessments providing oversight and guidance on major technical decisions across product engineering teams.
- Proactively manage technical debt balancing the need to move fast on product roadmap with maintaining high code quality, system reliability, and long-term platform health.
Engineering Delivery & Execution Excellence
- Lead the end-to-end engineering delivery of product roadmap translating product requirements into technical specifications, breaking down complex features, and driving execution across engineering teams.
- Establish and continuously improve engineering processes, development workflows, sprint ceremonies, code review practices, testing strategies, and deployment pipelines that maximize team velocity and product quality.
- Drive predictable, high-velocity product delivery ensuring engineering teams consistently ship high-quality features on schedule that meet product requirements and delight users.
- Monitor and optimize engineering velocity, deployment frequency, lead time, mean time to recovery (MTTR), and other key engineering performance metrics identifying bottlenecks and driving continuous improvement.
- Coordinate closely with Data Science/ML teams to integrate AI models, intelligent features, and decision support capabilities into products ensuring seamless collaboration between research and production engineering.
- Establish robust quality assurance practices including automated testing (unit, integration, end-to-end), performance testing, security testing, and user acceptance testing that ensure product excellence.
- Drive DevOps excellence and production reliability ensuring systems achieve enterprise-grade uptime, performance, scalability, security, and observability through robust SRE practices.
- Lead incident response, post-mortem analysis, and continuous improvement initiatives building a culture of operational excellence, learning from failures, and proactively preventing issues.
Education
- Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical field, or equivalent professional experience demonstrating deep technical expertise and leadership capability.
Experience
- 8+ years in software engineering with proven track record building and scaling SAAS products, including at least 3 years in senior engineering leadership roles managing multi-disciplinary engineering organizations.
- Demonstrated success leading product engineering teams that ship high-quality, customer-facing products at scale with measurable impact on business growth, user satisfaction, and product-market fit.
- Deep experience building multi-tenant SAAS platforms and cloud-native applications that serve enterprise customers with requirements for security, reliability, performance, and scalability.
- Proven track record of effective Product-Engineering partnership working collaboratively with Product Management, Product Design, and business stakeholders to deliver products that achieve strategic objectives.
- Experience leading engineering teams through significant growth phases scaling team size, improving engineering velocity, establishing best practices, and maintaining culture during periods of rapid expansion.
- Strong background in AI/ML product development, data-intensive applications, or intelligent systems with ability to bridge ML research and production engineering effectively.
- Track record of building high-performing engineering cultures characterized by technical excellence, innovation, ownership, collaboration, and continuous improvement.
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